System and method for automatically ranking lines of text

ABSTRACT

Disclosed are apparatus and methods for ranking lines of text. In one embodiment, an intent of a query is ascertained. A relevance of each one of a plurality of lines of text of a document is determined based upon the intent of the query, content of the query, and content of each of the plurality of lines of text. The plurality of lines of text may then be ranked according to the determined relevance of each of the plurality of lines of text.

BACKGROUND OF THE INVENTION

The present invention relates generally to computer implemented rankingof lines of text.

When a user submits a search query via a search engine, search enginemay present a list of search results. More specifically, the list ofsearch results typically lists a plurality of documents that satisfy thesearch query. When the search engine is implemented via a web site, eachof the documents may be identified by a corresponding Uniform ResourceLocator (URL).

When the search engine generates a list of search results, the searchengine typically generates a summary (i.e., abstract) of each document.Thus, for a single document, the search engine may present a title ofthe document, the summary that the web site has generated, and a URL atwhich the document may be accessed.

Unfortunately, the summary of a document is not always useful to theuser submitting the search query. As a result, the user mayunnecessarily click on documents that do not include the informationsought by the user. Alternatively, the user may choose not to click ondocuments that might be helpful to the user.

In view of the above, it would be beneficial if the summary of adocument could be generated in a more accurate manner in order toimprove the user experience.

SUMMARY OF THE INVENTION

Apparatus and methods for ranking lines of text are disclosed. Inaccordance with various embodiments, the intent of a query isascertained. A relevance of each one of a plurality of lines of text ofa document is determined based upon the intent of the query, content ofthe query, and content of each of the plurality of lines of text. Theplurality of lines of text may then be ranked according to thedetermined relevance of each of the plurality of lines of text.

In accordance with one embodiment, both a query-independent relevanceand a query-dependent relevance of each of the lines of text areascertained. A query-independent relevance of a line of text may bedefined as a degree to which the line of text of the document summarizesthe document. A query-dependent relevance of a line of text may bedefined as a relevance of the line of text to the query. The relevanceof a line of text may be determined based upon the query-independentrelevance, the query-dependent relevance of the line of text, and theintent of the query.

In accordance with another embodiment, the query-independent relevanceof a line of text may be established based upon variousquery-independent features that are analyzed within the line of text.Examples of query-independent features include the number of names inthe line of text or the placement of the line of text within thedocument (e.g., with respect to other lines of text in the document).Similarly, the query-dependent relevance of a line of text may beestablished based upon various query-dependent features that areanalyzed within the line of text. Examples of query-dependent featuresinclude the number of times each query term is found in the line of textor a percentage of the query terms that are found in the line of text.

In accordance with yet another embodiment, the intent of a query may beone of a variety of intents. For example, the intent of a query may benavigational if a user wishes to obtain directions to a particulardestination. As another example, the intent of a query may beinformational if the user wishes to merely obtain information regardinga particular topic.

In accordance with yet another embodiment, the query-independentrelevance of a line of text, the query-dependent relevance of the lineof text, and the intent of the query are expressed in the form of anumerical value. The relevance of each of the plurality of lines of textin a document may then be calculated based upon the intent of the query,the query-independent relevance of the corresponding line of text, andthe query-dependent relevance of the corresponding line of text. Forexample, the intent of the query may determine the weighting of thequery-independent relevance and the query-dependent relevance in thecalculation of the relevance of a line of text.

In accordance with yet another embodiment, the lines of text of adocument are ranked according to their relevance. Those lines of textthat are most relevant may then be used to generate a summary of thedocument.

In another embodiment, the invention pertains to a device comprising aprocessor, memory, and a display. The processor and memory areconfigured to perform one or more of the above described methodoperations. In another embodiment, the invention pertains to a computerreadable storage medium having computer program instructions storedthereon that are arranged to perform one or more of the above describedmethod operations.

These and other features and advantages of the present invention will bepresented in more detail in the following specification of the inventionand the accompanying figures which illustrate by way of example theprinciples of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an example system in whichvarious embodiments of the invention may be implemented.

FIG. 2A is a process flow diagram illustrating a generalized method ofranking lines of a document according to the intent of a query inaccordance with one embodiment of the invention.

FIG. 2B is a process flow diagram illustrating a specific method ofranking lines of a document according to the intent of a query inaccordance with one embodiment of the invention.

FIG. 2C is a process flow diagram illustrating a specific method ofranking lines of a document according to the intent of a query inaccordance with one embodiment of the invention.

FIG. 3 is a process flow diagram illustrating a method of ascertaining aquery independent relevance of lines of a document in accordance withone embodiment of the invention.

FIG. 4 is an example representation that may be generated by a queryindependent summarizer in order to ascertain the query-independentrelevance of lines of a document.

FIG. 5 is a process flow diagram illustrating a method of ascertaining aquery dependent relevance of lines of a document in accordance with oneembodiment of the invention.

FIG. 6 is an example representation that may be generated by a querydependent summarizer in order to ascertain the query-dependent relevanceof lines of a document.

FIG. 7 is an example representation that may be generated in order toascertain the intent of a query.

FIG. 8 is a simplified diagram of a network environment in whichspecific embodiments of the present invention may be implemented.

DETAILED DESCRIPTION OF THE SPECIFIC EMBODIMENTS

Reference will now be made in detail to specific embodiments of theinvention. Examples of these embodiments are illustrated in theaccompanying drawings. While the invention will be described inconjunction with these specific embodiments, it will be understood thatit is not intended to limit the invention to these embodiments. On thecontrary, it is intended to cover alternatives, modifications, andequivalents as may be included within the spirit and scope of theinvention as defined by the appended claims. In the followingdescription, numerous specific details are set forth in order to providea thorough understanding of the present invention. The present inventionmay be practiced without some or all of these specific details. In otherinstances, well known process operations have not been described indetail in order not to unnecessarily obscure the present invention.

A document typically includes a plurality of lines of text. Each line oftext may be a sentence, which may include any number of characters.Alternatively, each line of text may include a set of characters thatfills a single line of a page.

In order to generate a summary of a document to be presented in responseto a search query, the summary may be generated from a subset of thelines in the document. In one embodiment, a “relevance” of each of theplurality of lines may be ascertained, as will be described in furtherdetail below. The subset of lines having the most relevance may then beused to generate the summary. For example, the subset of lines may bepresented in order of relevance.

Various embodiments enable a summary of a document to be generated basedin part on the perceived intent of the query. More specifically, theperceived intent of a query may be used to assign a relevance to each ofthe plurality of lines in the document based upon the content of thequery and the content of the plurality of lines in the document. In thismanner, the relevance of the plurality of lines of text in the documentmay be used to identify a subset of the plurality of lines of text inthe document to be used in the summary.

FIG. 1 is a block diagram illustrating an example system in whichvarious embodiments of the invention may be implemented. When a query102 is submitted by a user, an Intent Classifier 104 may classify thequery 102 in order to determine an intent 106 of the query, as will bedescribed in further detail below. For instance, the intent may benavigational or informational. Thus, the intent of the query mayindicate a degree to which the query is navigational and/orinformational. More specifically, a navigational query may be a queryseeking directions to a specified destination (e.g., address or entity).Similarly, an informational query may be a query seeking information.

The intent 106 may be represented in the form of a numerical value,which may be a number between zero and one, inclusive. Thus, thenumerical value may indicate both a degree to which the query isnavigational and a degree to which the query is informational. Forexample, a number of zero may indicate that the query is entirelynavigational, while a number of one may indicate that the query isentirely informational (or vice versa). Thus, where the numerical valueis a number falling between zero and one, the numerical value mayindicate the degree to which the query is navigational, as well as thedegree to which the query is informational.

In addition, a Query Dependent Analyzer 108 may ascertain a querydependent relevance 110 of each of a plurality of lines of a document112 based upon the query 102 and the document 112. For example, a datastructure may be generated that includes each of the plurality of linesof the document 112 and a corresponding query dependent relevance 110for each of the plurality of lines of the document 112, as will bedescribed in further detail below. Each query dependent relevance value110 may be represented in the form of a numerical value.

A Query Independent Analyzer 114 may determine a query independentrelevance 116 of each of the plurality of lines of the document 112based on the contents of the document 112. For example, a data structuremay be generated that includes each of the plurality of lines of thedocument 112 and a corresponding query independent relevance 116 foreach of the plurality of lines of the document 112, as will be describedin further detail below. More specifically, the query independentrelevance 116 of a line of text is determined solely based upon thecontents of the document 112. In other words, the query independentrelevance 116 of a line of text is not determined based upon thecontents of the query 102. Each query independent relevance value 116may be represented in the form of a numerical value.

A Summarizer 118 may generate a summary 120 of the document 112 basedupon the intent 106, the query dependent relevance 110 of the lines oftext of the document 112, and the query independent relevance 116 of thelines of text of the document 112. More specifically, the Summarizer 118may generate a consolidated relevance value for each of the plurality oflines of text of the document 112 based upon the intent 106, the querydependent relevance 110 for the corresponding line of text, and thequery independent relevance 116 for the corresponding line of text. TheSummarizer 118 may then rank the plurality of lines of text according totheir corresponding consolidated relevance values.

FIG. 2A is a process flow diagram illustrating a generalized method ofranking lines of a document according to the intent of a query inaccordance with one embodiment of the invention. A perceived intent of aquery may be ascertained at 202. A relevance of each of a plurality oflines of text of a document may be determined based upon the intent ofthe query, content of the query, and content of each of the plurality oflines of text at 204. The plurality of lines of text may then be rankedaccording to the determined relevance of each of the plurality of linesof text at 206. In this manner, the plurality of lines may be ranked orsorted. A summary may then be generated using a subset of the pluralityof lines that have been determined to have the greatest relevance.

The subset of lines that are used to generate a summary may be selectedbased upon the desired length of the summary. The desired length of thesummary may be a pre-determined length, where the pre-determined lengthis a number of lines or characters. The pre-determined length may beascertained based upon a variety of factors, such as the source of thequery. For example, where the query has been received from a mobiledevice such as a cell phone, it may be desirable to generate a shortersummary. As a result, the pre-determined length may be selected from aset of pre-determined lengths appropriate for a variety ofcircumstances.

FIG. 2B is a process flow diagram illustrating a specific method ofranking lines of a document according to the intent of a query inaccordance with one embodiment of the invention. A degree to which eachof a plurality of lines of text of a document summarizes the documentmay be ascertained at 210. A relevance of each of the plurality of linesof text to the query may also be ascertained at 212. An intent of thequery may be ascertained at 214. A relevance of each of the plurality oflines of text of the document may then be ascertained at 216 basedupon 1) the intent of the query, 2) the relevance of the correspondingone of the plurality of lines of text to the query, and 3) the degree towhich the corresponding one of the plurality of lines of text summarizesthe document. The plurality of lines may then be automatically ranked at218 according to the ascertained relevance of each of the plurality oflines of text. A summary of the document may then be generated using asubset of the plurality of lines of text based upon the ranking of theplurality of lines of text.

FIG. 2C is a process flow diagram illustrating a specific method ofranking lines of a document according to the intent of a query inaccordance with one embodiment of the invention. A query-independentrelevance of each of a plurality of lines of text in a document may beascertained at 220. A query-dependent relevance of each of the pluralityof lines of text may be ascertained at 222. An intent of the query maybe ascertained at 224. A relevance of each one of the plurality of linesof text may be calculated based upon the intent of the query, the queryindependent relevance of the corresponding one of the plurality of linesof text and the query dependent relevance of the corresponding one ofthe plurality of lines of text at 226. The plurality of lines of textmay be ranked based upon the calculated relevance at 228. A summary ofthe document may then be generated using a subset of the plurality oflines of text based upon the ranking of the plurality of lines of text.

FIG. 3 is a process flow diagram illustrating a method of ascertaining aquery independent relevance of lines of a document as shown at 220 ofFIG. 2C in accordance with one embodiment of the invention. In order toascertain a query-independent relevance of the lines of text in adocument, the query-independent summarizer may divide the document intoa plurality of lines of text at 302. The query-independent summarizermay then identify a set of one or more query-independent features ineach of the plurality of lines of text at 304. The query-independentsummarizer may then ascertain a query-independent relevance from theidentified set of query-independent features at 306, as will bedescribed in further detail with reference to FIG. 4.

FIG. 4 is an example representation that may be generated by a queryindependent summarizer in order to ascertain the query-independentrelevance of lines of a document as described above with reference toFIG. 3. The representation may be generated in the form of a datastructure such as a table. In this example, each row (i.e., entry) 402in the table corresponds to a different line of the document. Each ofthe set of query-independent features may be represented by a differentcolumn of the table. Specifically, each of the set of query-independentfeatures may identify a different piece of query-independent datacollected from a line. In other words, each of the set ofquery-independent features is not dependent upon a query that has beensubmitted.

Examples of various query-independent features are shown as Features1-3. Specifically, Feature 1 404 indicates how common one or more wordsin the line are. For instance, a database may be accessed to ascertain afrequency with which various words are typically used. Of course, suchdeterminations may exclude various words, such as “the,” “and,” and“or.” Feature 2 406 indicates a number of names in the correspondingline. For instance, the existence of one or more names may indicategreater relevance of the line to the document. Feature 3 408 indicates aposition of a line within the document. More specifically, placement ofa line within the document may indicate importance and thereforerelevance of the line to the document. For example, the position of theline within the document may indicate that the line falls within thebeginning of the document, the middle of the document, the end of thedocument, the first line of a paragraph, the middle of a paragraph, orthe last line of a paragraph. Thus, one or more query independentfeatures may indicate whether the line of text is the first line of aparagraph and/or whether the line of text is the first line of thedocument. Each of the features 404-408 of a line may be represented by anumerical value.

It is important to note that the features 404-408 are merely examples,and therefore other query-independent features may be considered inaddition to, or instead of, those shown in FIG. 4. For instance, one ormore query independent features may indicate the number of words in theline of text and/or the number of common words (e.g., a, and, the) inthe line of text.

From the identified features 404-408, a total query-independentrelevance 410 of a line may be ascertained. For example, the totalquery-independent relevance 410 of a line may be calculated usingnumerical values for the identified features 404-408 for that line.Alternatively, values of the features for a line may be used toascertain the line's query-independent relevance via a lookup table orpattern matching. For example, the pattern of values of the features fora line may be matched against a set of rules and/or patterns stored in afile or database. The set of rules and/or patterns may be manuallyconfigured and/or may be system generated. Moreover, the system maylearn further rules and/or patterns. For example, the system maygenerate various rules and/or patterns from a pre-configured set ofrules and/or patterns. As another example, the system may generalizerules and/or patterns from various examples. For instance, the systemmay analyze a document and corresponding abstract to identify whichlines of the document were used to generate the abstract, enabling thesystem to generate a set of rules and/or patterns that may be used toidentify these lines.

FIG. 5 is a process flow diagram illustrating a method of ascertaining aquery dependent relevance of lines of a document as shown at 222 of FIG.2C in accordance with one embodiment of the invention. In order toascertain a query-dependent relevance of the lines of text in adocument, the query-dependent summarizer may divide the document into aplurality of lines of text at 502. The query-dependent summarizer maythen identify a set of one or more query-dependent features in each ofthe plurality of lines of text at 504. The query-dependent summarizermay then ascertain a query-dependent relevance from the identified setof query-dependent features at 506, as will be described in furtherdetail with reference to FIG. 6.

FIG. 6 is an example representation that may be generated by a querydependent summarizer in order to ascertain the query-dependent relevanceof lines of a document as described above with reference to FIG. 5. Therepresentation may be generated in the form of a data structure such asa table. In this example, each row (i.e., entry) 602 in the tablecorresponds to a different line of the document. Each of the set ofquery-dependent features may be represented by a different column of thetable. Specifically, each of the set of query-dependent features mayidentify a different piece of query-dependent data collected from a lineusing the submitted query.

Examples of various query-dependent features are shown as Features 1-2.Specifically, Feature 1 604 indicates a percentage of the query termsthat are found in the corresponding line. Feature 2 606 indicates anumber of times a particular query term is found in the line. Thus,feature 2 606 may be ascertained for each of the query terms in thepreviously submitted query. Feature 3 608 may indicate whether the queryis a substring of the line of text. It is important to note that thequery-dependent features described with reference to FIG. 6 are merelyexamples. Therefore, other query-dependent features such as thepercentage of query terms and their synonyms that occur in the line oftext may also be considered. Each of the features 604-608 of a line maybe represented by a numerical value.

From the identified features 604-608, a total query-dependent relevance610 of a line may be ascertained. For example, the total query-dependentrelevance 610 of a line may be calculated using numerical values for theidentified features 604-608 for that line. Alternatively, a pattern ofvalues of the features for a line may be used to ascertain itsrelevance. For example, the pattern of values of the features for a linemay be matched against a set of rules and/or patterns stored in a fileor database. The set of rules and/or patterns may be manually configuredand/or may be system generated. Moreover, the system may learn furtherrules and/or patterns. For example, the system may generate variousrules and/or patterns from a pre-configured set of rules and/orpatterns. As another example, the system may generalize rules and/orpatterns from various examples. For instance, the system may analyze adocument and corresponding abstract to identify which lines of thedocument were used to generate the abstract, enabling the system togenerate a set of rules and/or patterns that may be used to identifythese lines.

FIG. 7 is an example representation that may be generated in order toascertain the intent of a query as set forth above with reference to 224of FIG. 2C. The representation may be generated in the form of a datastructure such as a table. In this example, each row (i.e., entry) 702in the table corresponds to a different query. Each of a set of featuresused to determine the intent of a query may be represented by adifferent column of the table.

Examples of various features used to determine the intent of a query areshown as Features 1-2. Specifically, Feature 1 704 indicates whether thequery includes one or more names. More specifically, the inclusion of aname in a query may indicate that the query is navigational, rather thaninformational. Thus, one or more features may indicate whether the querycontains an organization name and/or a product name. Feature 2 706indicates click characteristics associated with the query. For instance,the click characteristics may indicate the percentage of times that auser will click on a document corresponding to the name provided in thequery when the query is submitted. Feature 3 708 may indicate the numberof words in the query. Each of the features 704-708 of a line may berepresented by a numerical value.

From the identified features 704-708, an intent 710 of a query may beascertained. For example, the intent 710 of a query may be calculatedusing numerical values for the identified features 704-708 for thecorresponding line. Alternatively, a pattern of values of the featuresfor a line corresponding to a query may be used to ascertain acorresponding intent. For example, the pattern of values of the featuresfor a query may be matched against a set of rules and/or patterns storedin a file or database. The set of rules and/or patterns may be manuallyconfigured and/or may be system generated. Moreover, the system maylearn further rules and/or patterns. For example, the system maygenerate various rules and/or patterns from a pre-configured set ofrules and/or patterns. As another example, the system may generalizerules and/or patterns from various examples.

In one embodiment, the intent of the query is represented by a numericalvalue. For instance, the intent of the query may be represented by avalue between zero and one, inclusive. In a specific embodiment, wherethe value is equal to one, the intent of the query is navigational andwhere the value is equal to zero, the intent of the query isinformational. Alternatively, it is possible to assign a value of one toinformational queries and a value of zero to navigational queries.

Once the query-independent relevance of a line, the query-dependentrelevance of a line, and the intent of the query have been ascertained,a total relevance of the line may be calculated as set forth above withreference to 226 of FIG. 2C. In one embodiment, this may be accomplishedby applying the following Equation:αF _(I)(1)+(1−α)F _(Q)(1,q)=Relevance,

where α=Intent of query

F_(I)(1)=Query-independent relevance of line, based upon contents of theline

F_(Q)(1,q)=Query-dependent relevance of line, based upon contents of theline and the query

Thus, in this example, the calculation of the relevance of a line willyield a numerical value between zero and one, where the value indicatesa degree to which the intent of the query is informational and/ornavigational. In this manner, the intent of a query may be used toassign a “weighting value” to the query-dependent relevance and thequery-independent relevance of a line of text in order to ascertain atotal relevance of the line of text.

Embodiments of the present invention may be employed in any of a widevariety of computing contexts to ascertain the relevance of lines oftext to a document, ranking the lines of text of the document accordingto the ascertained relevance and/or generate a summary of the documentusing a subset of the lines of text of the document according to themanner in which they have been ranked. For example, as illustrated inFIG. 8, implementations are contemplated in which the relevantpopulation of users interact with a diverse network environment via anytype of computer (e.g., desktop, laptop, tablet, etc.) 1002, mediacomputing platforms 1003 (e.g., cable and satellite set top boxes anddigital video recorders), handheld computing devices (e.g., PDAs) 1004,cell phones 1006, or any other type of computing or communicationplatform.

And according to various embodiments, input that is processed inaccordance with the invention may be obtained using a wide variety oftechniques. For example, a user search query may be obtained from auser's interaction with a local application, web site or web-basedapplication or service and may be accomplished using any of a variety ofwell known mechanisms for obtaining information from a user. However, itshould be understood that such methods of obtaining input from a userare merely examples and that a search query may be obtained in manyother ways.

This is represented in FIG. 8 by server 1008 and data store 1010 which,as will be understood, may correspond to multiple distributed devicesand data stores. The invention may also be practiced in a wide varietyof network environments (represented by network 1012) including, forexample, TCP/IP-based networks, telecommunications networks, wirelessnetworks, etc. In addition, the computer program instructions with whichembodiments of the invention are implemented may be stored in any typeof computer-readable media, and may be executed according to a varietyof computing models including a client/server model, a peer-to-peermodel, on a stand-alone computing device, or according to a distributedcomputing model in which various of the functionalities described hereinmay be effected or employed at different locations.

The disclosed techniques of the present invention may be implemented inany suitable combination of software and/or hardware system, such as aweb-based server or desktop computer system. The line ranking andsummary generating apparatus of this invention may be speciallyconstructed for the required purposes, or it may be a general-purposecomputer selectively activated or reconfigured by a computer programand/or data structure stored in the computer. The processes presentedherein are not inherently related to any particular computer or otherapparatus. In particular, various general-purpose machines may be usedwith programs written in accordance with the teachings herein, or it maybe more convenient to construct a more specialized apparatus to performthe required method steps.

Regardless of the system's configuration, it may employ one or morememories or memory modules configured to store data, programinstructions for the general-purpose processing operations and/or theinventive techniques described herein. The program instructions maycontrol the operation of an operating system and/or one or moreapplications, for example. The memory or memories may also be configuredto store data structures for analyzing query-dependent features andquery-independent features of lines of text, rules and/or patterns foranalyzing various query-dependent features for generating aquery-dependent relevance, rules and/or patterns for analyzing variousquery-independent features for generating a query-independent relevance,etc.

Because such information and program instructions may be employed toimplement the systems/methods described herein, the present inventionrelates to machine readable media that include program instructions,state information, etc. for performing various operations describedherein. Examples of machine-readable media include, but are not limitedto, magnetic media such as hard disks, floppy disks, and magnetic tape;optical media such as CD-ROM disks; magneto-optical media such asfloptical disks; and hardware devices that are specially configured tostore and perform program instructions, such as read-only memory devices(ROM) and random access memory (RAM). Examples of program instructionsinclude both machine code, such as produced by a compiler, and filescontaining higher level code that may be executed by the computer usingan interpreter.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications may be practiced within the scope of theappended claims. Therefore, the present embodiments are to be consideredas illustrative and not restrictive and the invention is not to belimited to the details given herein, but may be modified within thescope and equivalents of the appended claims.

1. A method, comprising: ascertaining an intent of a query; determiningby a processor a relevance of each one of a plurality of lines of textof a document based upon the intent of the query, content of the query,and content of each of the plurality of lines of text, wherein thedocument is a single search result returned in response to the query;ranking the plurality of lines of text according to the determinedrelevance of each of the plurality of lines of text; and generating asummary of the single search result using a subset of the plurality oflines of text based upon the ranking of the plurality of lines of text.2. The method as recited in claim 1, wherein determining a relevance ofeach one of a plurality of lines of text of a document based upon theintent of the query, content of the query, and content of each of theplurality of lines of text comprises: ascertaining a degree to whicheach of the plurality of lines of text of the document summarizes thedocument; determining a query-dependent relevance of each of theplurality of lines of text to the query; and ascertaining the relevanceof each one of the plurality of lines of text of the document based uponthe intent of the query, the query-dependent relevance of the one of theplurality of lines of text to the query, and the degree to which the oneof the plurality of lines of text summarizes the document.
 3. The methodas recited in claim 1, wherein determining a relevance of each one of aplurality of lines of text of a document based upon the intent of thequery, content of the query, and content of each of the plurality oflines of text comprises: determining a query-independent relevance ofeach of the plurality of lines of text in the document; determining aquery-dependent relevance of each of the plurality of lines of text inthe document; and calculating the relevance of each one of the pluralityof lines of text based upon the intent of the query, the queryindependent relevance of the one of the plurality of lines of text inthe document and the query dependent relevance of the one of theplurality of lines of text in the document.
 4. The method as recited inclaim 3, wherein determining a query-independent relevance of each ofthe plurality of lines of text in the document includes identifying aset of one or more query-independent features in each of the pluralityof lines of text in the document, and wherein determining aquery-dependent relevance of each of the plurality of lines of text inthe document includes identifying a set of one or more query-dependentfeatures in each of the plurality of lines of text in the document. 5.The method as recited in claim 1, further comprising: presenting thesummary of the document in association with a Uniform Resource Locator(URL) of the document.
 6. The method as recited in claim 1, wherein theintent of the query indicates a degree to which the query isnavigational or informational.
 7. The method as recited in claim 1,wherein ascertaining the intent of the query comprises: obtaining anumerical value that indicates both a degree to which the query isnavigational and a degree to which the query is informational.
 8. Themethod as recited in claim 7, wherein the numerical value is a numberbetween zero and one.
 9. An apparatus, comprising: a processor; and amemory, at least one of the processor or the memory being adapted for:ascertaining an intent of a query; determining a relevance of each oneof a plurality of lines of text of a document based upon the intent ofthe query, content of the query, and content of each of the plurality oflines of text, wherein the document is a single search result returnedin response to the query; ranking the plurality of lines of textaccording to the determined relevance of each of the plurality of linesof text; and generating a summary of the single search result using asubset of the plurality of lines of text based upon the ranking of theplurality of lines of text.
 10. The apparatus as recited in claim 9,wherein determining a relevance of each one of a plurality of lines oftext of a document based upon the intent of the query, content of thequery, and content of each of the plurality of lines of text comprises:ascertaining a degree to which each of the plurality of lines of text ofthe document summarizes the document; determining a query-dependentrelevance of each of the plurality of lines of text to the query; andascertaining the relevance of each one of the plurality of lines of textof the document based upon the intent of the query, the query-dependentrelevance of the one of the plurality of lines of text to the query, andthe degree to which the one of the plurality of lines of text summarizesthe document.
 11. The apparatus as recited in claim 9, whereindetermining a relevance of each one of a plurality of lines of text of adocument based upon the intent of the query, content of the query, andcontent of each of the plurality of lines of text comprises: determininga query-independent relevance of each of the plurality of lines of textin the document; determining a query-dependent relevance of each of theplurality of lines of text in the document; and calculating therelevance of each one of the plurality of lines of text based upon theintent of the query, the query independent relevance of the one of theplurality of lines of text in the document and the query dependentrelevance of the one of the plurality of lines of text in the document.12. The apparatus as recited in claim 11, wherein determining aquery-independent relevance of each of the plurality of lines of text inthe document includes identifying a set of one or more query-independentfeatures in each of the plurality of lines of text in the document, andwherein determining a query-dependent relevance of each of the pluralityof lines of text in the document includes identifying a set of one ormore query-dependent features in each of the plurality of lines of textin the document.
 13. The apparatus as recited in claim 9, wherein theintent of the query indicates a degree to which the query isnavigational or informational.
 14. The apparatus as recited in claim 9,wherein ascertaining the intent of the query comprises: obtaining anumerical value that indicates both a degree to which the query isnavigational and a degree to which the query is informational.
 15. Theapparatus as recited in claim 14, wherein the numerical value is anumber between zero and one.
 16. The apparatus as recited in claim 9, atleast one of the processor or the memory being further adapted forperforming the determining, ranking, and generating steps for each of aplurality of documents, the plurality of documents being search resultsreturned in response to the query.
 17. The apparatus as recited in claim16, the method further comprising: for each of the plurality ofdocuments, presenting the summary and a Uniform Resource Locator (URL)of the corresponding one of the plurality of documents.
 18. Acomputer-readable medium storing thereon computer-readable instructions,comprising: instructions for ascertaining an intent of a query;instructions for determining a relevance of each one of a plurality oflines of text of a document based upon the intent of the query, contentof the query, and content of each of the plurality of lines of text,wherein the document is a single search result returned in response tothe query; instructions for ranking the plurality of lines of textaccording to the determined relevance of each of the plurality of linesof text; and instructions for generating a summary of the single searchresult using a subset of the plurality of lines of text based upon theranking of the plurality of lines of text.
 19. The computer-readablemedium as recited in claim 18, wherein the instructions for determininga relevance of each one of a plurality of lines of text of a documentbased upon the intent of the query, content of the query, and content ofeach of the plurality of lines of text comprises: instructions forascertaining a degree to which each of the plurality of lines of text ofthe document summarizes the document; instructions for determining aquery-dependent relevance of each of the plurality of lines of text tothe query; and instructions for ascertaining the relevance of each oneof the plurality of lines of text of the document based upon the intentof the query, the query-dependent relevance of the one of the pluralityof lines of text to the query, and the degree to which the one of theplurality of lines of text summarizes the document.
 20. Thecomputer-readable medium as recited in claim 18, wherein theinstructions for determining a relevance of each one of a plurality oflines of text of a document based upon the intent of the query, contentof the query, and content of each of the plurality of lines of textcomprises: instructions for determining a query-independent relevance ofeach of the plurality of lines of text in the document; instructions fordetermining a query-dependent relevance of each of the plurality oflines of text in the document; and instructions for calculating therelevance of each one of the plurality of lines of text based upon theintent of the query, the query independent relevance of the one of theplurality of lines of text in the document and the query dependentrelevance of the one of the plurality of lines of text in the document.21. The computer-readable medium as recited in claim 20, whereindetermining a query-independent relevance of each of the plurality oflines of text in the document includes identifying a set of one or morequery-independent features in each of the plurality of lines of text inthe document, and wherein determining a query-dependent relevance ofeach of the plurality of lines of text in the document includesidentifying a set of one or more query-dependent features in each of theplurality of lines of text in the document.
 22. The computer-readablemedium as recited in claim 18, wherein the intent of the query indicatesa degree to which the query is navigational or informational.
 23. Thecomputer-readable medium as recited in claim 18, wherein ascertainingthe intent of the query comprises: obtaining a numerical value thatindicates both a degree to which the query is navigational and a degreeto which the query is informational.
 24. The computer-readable medium asrecited in claim 23, wherein the numerical value is a number betweenzero and one.